Deep learning in medical image registration: a review
This paper presents a review of deep learning (DL)-based medical image registration
methods. We summarized the latest developments and applications of DL-based registration …
methods. We summarized the latest developments and applications of DL-based registration …
Weakly supervised machine learning
Supervised learning aims to build a function or model that seeks as many mappings as
possible between the training data and outputs, where each training data will predict as a …
possible between the training data and outputs, where each training data will predict as a …
Patient-specific reconstruction of volumetric computed tomography images from a single projection view via deep learning
Tomographic imaging using penetrating waves generates cross-sectional views of the
internal anatomy of a living subject. For artefact-free volumetric imaging, projection views …
internal anatomy of a living subject. For artefact-free volumetric imaging, projection views …
Volumetric tumor tracking from a single cone-beam X-ray projection image enabled by deep learning
Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the
accuracy of radiotherapy is significantly compromised due to respiratory-induced …
accuracy of radiotherapy is significantly compromised due to respiratory-induced …
GPU-based high-performance computing for radiation therapy
Recent developments in radiotherapy therapy demand high computation powers to solve
challenging problems in a timely fashion in a clinical environment. The graphics processing …
challenging problems in a timely fashion in a clinical environment. The graphics processing …
DeepOrganNet: on-the-fly reconstruction and visualization of 3D/4D lung models from single-view projections by deep deformation network
This paper introduces a deep neural network based method, ie, DeepOrganNet, to generate
and visualize fully high-fidelity 3D/4D organ geometric models from single-view medical …
and visualize fully high-fidelity 3D/4D organ geometric models from single-view medical …
Cine cone beam CT reconstruction using low-rank matrix factorization: algorithm and a proof-of-principle study
Respiration-correlated CBCT, commonly called 4DCBCT, provides respiratory phase-
resolved CBCT images. A typical 4DCBCT represents averaged patient images over one …
resolved CBCT images. A typical 4DCBCT represents averaged patient images over one …
Deformer: Towards displacement field learning for unsupervised medical image registration
Recently, deep-learning-based approaches have been widely studied for deformable image
registration task. However, most efforts directly map the composite image representation to …
registration task. However, most efforts directly map the composite image representation to …
2D/3D non-rigid image registration via two orthogonal X-ray projection images for lung tumor tracking
Two-dimensional (2D)/three-dimensional (3D) registration is critical in clinical applications.
However, existing methods suffer from long alignment times and high doses. In this paper, a …
However, existing methods suffer from long alignment times and high doses. In this paper, a …
Simultaneous motion estimation and image reconstruction (SMEIR) for 4D cone‐beam CT
Purpose: Image reconstruction and motion model estimation in four‐dimensional cone‐
beam CT (4D‐CBCT) are conventionally handled as two sequential steps. Due to the limited …
beam CT (4D‐CBCT) are conventionally handled as two sequential steps. Due to the limited …